Three years ago, a novel association between myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and the murine retrovirus XMRV was published.[1] Since then, 191 papers have been published on the subject (NCBI PubMed, accessed 6 November 2012), largely disproving the initial association, a trend confirmed by a recent multicentre blinded trial which definitively concluded that there is no association between ME/CFS and XMRV.[2] It is therefore time to revisit the investigation of ME/CFS aetiology. Metagenomics offers a promising new opportunity for hypothesis discovery in microbial associations with ME/CFS, and we describe herein the technical basis of this approach and its advantages in aetiological agent investigation.

Metagenomics: a brief primer

Metagenomics is the analysis of all nucleic acid recovered directly from a clinical or environmental sample. Using next-generation sequencing platforms, researchers can sequence the DNA of an entire sample, generating multiple short sequences known as “reads.” Computational techniques can then be used to identify the microbes present in the sample (the “microbiome”) and their relative abundance. Improvements in sequencing platforms have brought the cost of a typical metagenomics sample to under $200, resulting in an increasing number of metagenomics-based analyses in the literature. A complete microbial census of various body sites was performed on 250 human volunteers as part of the Human Microbiome Project,[3] while subsequent “metagenome-wide association studies” (MGWAS) have compared the microbiomes of healthy individuals to those with various conditions. Amongst other findings, these data have identified associations between inflammatory bowel disease and enterobacteriaceae,[4] colorectal carcinoma and fusobacterium,[5] and type two diabetes and butyrate-producing bacteria.[6]

Metagenomics for ME/CFS

Metagenomics offers an unbiased opportunity to investigate potential novel associations between microbes and ME/CFS. Unlike previous studies, which have examined the host immune response, response to antimicrobial treatment regimens, or used PCR-based screening, a metagenomics protocol replaces the reductionist search for a specific agent with a more holistic discovery-oriented strategy capable of revealing associations with new candidate aetiological agents, including novel pathogens. Metagenomics also offers several other advantages relative to other experimental approaches, summarised in Table 1. These include technical advantages, such as the elimination of a culture step and the ability to detect low-abundance microorganisms. More general opportunities include the ability to investigate the role of microbial communities and/or functional networks in ME/CFS as opposed to an individual species.

The metagenomics approach is also unique in that even a negative result is of use. Presuming a study is performed with sufficient power and scientific rigour, metagenomics has the potential to detect any microbe in a sample; therefore the lack of observed associations between ME/CFS and microbial entities would provide strong, albeit not conclusive, evidence that the origins of ME/CFS lie in non-infectious causes. However, it must be noted that metagenomics is not able to prove that a disease was instigated by a microbe if it has since been removed from the body site of investigation. Nevertheless, even if the causal microbe is no longer present, it may have changed the composition of the microbiome, by altering the presence or relative abundance of other microbes. Such changes could be detected by metagenomics and be used to diagnose and, in principle, treat the symptoms of ME/CFS, even if not the initial cause.